Systematic Differences in Bucket Sea Surface Temperature Measurements among Nations Identified Using a Linear-Mixed-Effect Method

Abstract

The International Comprehensive Ocean–Atmosphere Dataset (ICOADS) is a cornerstone for estimating changes in sea surface temperatures (SST) over the instrumental era. Interest in determining SST changes to within 0.1°C makes detecting systematic offsets within ICOADS important. Previous studies have corrected for offsets among engine room intake, buoy, and wooden and canvas bucket measurements, as well as noted discrepancies among various other groupings of data. In this study, a systematic examination of differences in collocated bucket SST measurements from ICOADS3.0 is undertaken using a linear-mixed-effect model according to nations and more-resolved groupings. Six nations and a grouping for which nation metadata are missing, referred to as “deck 156,” together contribute 91% of all bucket measurements and have systematic offsets among one another of as much as 0.22°C. Measurements from the Netherlands and deck 156 are colder than the global average by −0.10° and −0.13°C, respectively, both at p < 0.01, whereas Russian measurements are offset warm by 0.10°C at p < 0.1. Furthermore, of the 31 nations whose measurements are present in more than one grouping of data (i.e., deck), 14 contain decks that show significant offsets at p < 0.1, including all major collecting nations. Results are found to be robust to assumptions regarding the independence and distribution of errors as well as to influences from the diurnal cycle and spatially heterogeneous noise variance. Correction for systematic offsets among these groupings should improve the accuracy of estimated SSTs and their trends.

Causes of climate change over the historical record

“…Gridded global instrumental surface temperature data sets presently stretch to 1850, with estimates of uncertainty available that include both the effect of sampling uncertainty and systematic changes in measurement techniques, such as different types of buckets (Folland and Parker 1995). While the record is fairly well researched, issues continue to be discovered, such as an inhomogeneity in SST data in the 1940s (Thompson et al 2008); and ongoing offsets due to differences in observing fleets (Chan and Huybers 2019). Long, homogenized instrumental surface temperature records go back to the 18th century for some European locations such as Milan, Stockholm, and Central England, resolving daily variability (e.g.…”

“…To what extent this discrepancy is due to model error, residual forcing or remaining observational error in SSTs (Chan andHuybers 2019, Haustein et al 2019) is presently unclear (Friedman et al in revision). The difference between variability with multimodel mean removed compared to that from control simulations ( figure 8(c)) suggests that residual forcing may have contributed to the variability in observations.…”

An Ensemble Data Set of Sea Surface Temperature Change From 1850: The Met Office Hadley Centre HadSST.4.0.0.0 Data Set

“…In contrast, Kent and Kaplan (2006) and Carella, Morris, et al (2017) focused on situations in which solar heating was negligible. Recently, Chan and Huybers (2019) showed that there are relative biases between bucket measurements made by ships from different countries and between bucket measurements found in different decks in ICOADS. They argue that correcting for biases between decks and nations should improve estimated SSTs.…”

ACSIS Atlantic Ocean medium resolution SST dataset: Reconstructed 5‐day, ½‐degree, Atlantic Ocean SST (1950‐2014)

“…Recent work by others has included the examination of biases in different types of buckets (e.g. Carella et al ., 2017; Chan and Huybers, 2019).…”